The best way then to not create duplicates is to look at all existing organizations in Wikidata and add the court and court number manually, if they are German and then exclude these from the import.
Guarantees that there will be no duplicates.
So the technical side is feasible. Barriers are political and legal.
Sebastian
Am 16. Oktober 2017 14:24:51 MESZ schrieb Sebastian Hellmann hellmann@informatik.uni-leipzig.de:
Ah yes, forgot to mention:
there is no URI or unique identifier given by the Handelsregister system. However, the courts take care that the registrations are unique, so it is implicit. Handelsregister could easily create stable URIs out of the court+type+number like /Leipzig_HRB_32853
For Wikidata this is not a problem to handle. So no technical issues from this side either.
All the best,
Sebastian
On 16.10.2017 13:41, Sebastian Hellmann wrote:
Hi all,
the technical challenges are not so difficult.
- 2.2 million are the exact number of German organisations, i.e.
associations and companies. They are also unique.
- Wikidata has 40k organisations:
https://query.wikidata.org/#SELECT %3Fitem %3FitemLabel %0AWHERE %0A{%0A %3Fitem wdt%3AP31 wd%3AQ43229.%0A SERVICE wikibase%3Alabel { bd%3AserviceParam wikibase%3Alanguage "[AUTO_LANGUAGE]%2Cen". }%0A}
so there would be a maximum of 40k duplicates These are easy to find and deduplicate
- The crawl can be done easily, a colleague has done so before.
The issues here are:
- Do you want to upload the data in Wikidata? It would be a real big
extension. Can I go ahead
- If the data were available externally as structured data under open
license, I would probably not suggest loading it into wikidata, as
the
data can be retrieved from the official source directly, however,
here
this data will not be published in a decent format.
I thought that the way data is copied from coyrighted sources, i.e. only facts is ok for wikidata. This done in a lot of places, I guess.
Same for Wikipedia, i.e. News articles and copyrighted books are referenced. So Wikimedia or the Wikimedia community are experts on
this.
All the best,
Sebastian
On 16.10.2017 10:18, Neubert, Joachim wrote:
Hi Sebastian,
This is huge! It will cover almost all currently existing German companies. Many of these will have similar names, so preparing for disambiguation is a concern.
A good way for such an approach would be proposing a property for an
external identifier, loading the data into Mix-n-match, creating links for companies already in Wikidata, and adding the rest (or perhaps only parts of them - I’m not sure if having all of them in Wikidata makes sense, but that’s another discussion), preferably
with
location and/or sector of trade in the description field.
I’ve tried to figure out what could be used as key for a external identifier property. However, it looks like the registry does not offer any (persistent) URL to its entries. So for looking up a company, apparently there are two options:
-conducting an extended search for the exact string “A&A Dienstleistungsgesellschaft mbH“
-copying the register number “32853” plus selecting the court (Leipzig) from the according dropdown list and search that
Both ways are not very intuitive, even if we can provide a link to the search form. This would make a weak connection to the source of information. Much more important, it makes disambiguation in Mix-n-match difficult. This applies for the preparation of your initial load (you would not want to create duplicates). But much
more
so for everybody else who wants to match his or her data later on. Being forced to search for entries manually in a cumbersome way for disambiguation of a new, possibly large and rich dataset is, in my eyes, not something we want to impose on future contributors. And often, the free information they find in the registry (formal name, register number, legal form, address) will not easily match with the
information they have (common name, location, perhaps founding date,
and most important sector of trade), so disambiguation may still be difficult.
Have you checked which parts of the accessible information as below can be crawled and added legally to external databases such as
Wikidata?
Cheers, Joachim
--
Joachim Neubert
ZBW – German National Library of Economics
Leibniz Information Centre for Economics
Neuer Jungfernstieg 21 20354 Hamburg
Phone +49-42834-462
*Von:*Wikidata [mailto:wikidata-bounces@lists.wikimedia.org] *Im Auftrag von *Sebastian Hellmann *Gesendet:* Sonntag, 15. Oktober 2017 09:45 *An:* wikidata@lists.wikimedia.org
mailto:wikidata@lists.wikimedia.org
*Betreff:* [Wikidata] Kickstartet: Adding 2.2 million German organisations to Wikidata
Hi all,
the German business registry contains roughly 2.2 million organisations. Some information is paid, but other is public, i.e. the info you are searching for at and clicking on UT (see example
below):
https://www.handelsregister.de/rp_web/mask.do?Typ=e
I would like to add this to Wikidata, either by crawling or by raising money to use crowdsourcing concepts like crowdflour or
amazon
turk.
It should meet notability criteria 2: https://www.wikidata.org/wiki/Wikidata:Notability
2. It refers to an instance of a *clearly identifiableconceptual
or material entity*. The entity must be notable, in the sense that it *can be described using serious and publicly available references*. If there is no item about you yet, you are probably not notable.The reference is the official German business registry, which is serious and public. Orgs are also per definition clearly
identifiable
legal entities.
How can I get clearance to proceed on this?
All the best, Sebastian
Entity dataSaxony District court *Leipzig HRB 32853 * – A&A Dienstleistungsgesellschaft mbH
Legal status:
Gesellschaft mit beschränkter Haftung
Capital:
25.000,00 EUR
Date of entry:
29/08/2016 (When entering date of entry, wrong data input can occur due to system failures!)
Date of removal:
Balance sheet available:
Address (subject to correction):
A&A Dienstleistungsgesellschaft mbH Prager Straße 38-40
04317 Leipzig
-- All the best, Sebastian Hellmann
Director of Knowledge Integration and Linked Data Technologies
(KILT)
Competence Center at the Institute for Applied Informatics (InfAI) at Leipzig
University
Executive Director of the DBpedia Association Projects: http://dbpedia.org, http://nlp2rdf.org, http://linguistics.okfn.org, https://www.w3.org/community/ld4lt http://www.w3.org/community/ld4lt Homepage: http://aksw.org/SebastianHellmann Research Group: http://aksw.org
Wikidata mailing list Wikidata@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wikidata
-- All the best, Sebastian Hellmann
Director of Knowledge Integration and Linked Data Technologies (KILT)
Competence Center at the Institute for Applied Informatics (InfAI) at Leipzig
University
Executive Director of the DBpedia Association Projects: http://dbpedia.org, http://nlp2rdf.org, http://linguistics.okfn.org, https://www.w3.org/community/ld4lt http://www.w3.org/community/ld4lt Homepage: http://aksw.org/SebastianHellmann Research Group: http://aksw.org
Wikidata mailing list Wikidata@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wikidata
-- All the best, Sebastian Hellmann
Director of Knowledge Integration and Linked Data Technologies (KILT) Competence Center at the Institute for Applied Informatics (InfAI) at Leipzig University Executive Director of the DBpedia Association Projects: http://dbpedia.org, http://nlp2rdf.org, http://linguistics.okfn.org, https://www.w3.org/community/ld4lt http://www.w3.org/community/ld4lt Homepage: http://aksw.org/SebastianHellmann Research Group: http://aksw.org